The neural signature of the decision value of future pain.

Pain is a primary driver of action. We often must voluntarily accept pain to gain rewards. Conversely, we may sometimes forego potential rewards to avoid associated pain. In this study, we investigated how the brain represents the decision value of future pain. Participants (n = 57) performed an economic decision task, choosing to accept or reject offers combining various amounts of pain and money presented visually. Functional MRI (fMRI) was used to measure brain activity throughout the decision-making process. Using multivariate pattern analyses, we identified a distributed neural representation predicting the intensity of the potential future pain in each decision and participants' decisions to accept or avoid pain. This neural representation of the decision value of future pain included negative weights located in areas related to the valuation of rewards and positive weights in regions associated with saliency, negative affect, executive control, and goal-directed action. We further compared this representation to future monetary rewards, physical pain, and aversive pictures and found that the representation of future pain overlaps with that of aversive pictures but is distinct from experienced pain. Altogether, the findings of this study provide insights on the valuation processes of future pain and have broad potential implications for our understanding of disorders characterized by difficulties in balancing potential threats and rewards.

Starting the pill during adolescence: Age of onset and duration of use influence morphology of the hippocampus and ventromedial prefrontal cortex.

From adolescence, women become more likely to experience fear dysregulation. Oral contraceptives (OCs) can modulate the brain regions involved in fear processes. OCs are generally used for years and often initiated during adolescence, a sensitive period where certain brain regions involved in the fear circuitry are still undergoing important reorganization. It remains unknown whether OC use during adolescence may induce long-lasting changes in the fear circuitry. This study aimed to examine whether age of onset moderated the relationship between duration of use and fear-related brain structures. We collected structural MRI data in 98 healthy adult women (61 current users, 37 past users) and extracted grey matter volumes (GMV) and cortical thickness (CT) of key regions of the fear circuitry. Non-linear multiple regressions revealed interaction effects between age of onset and quadratic duration of use on GMV of the right hippocampus and right ventromedial prefrontal cortex (vmPFC). Among women who initiated OCs earlier in adolescence, a short duration of use was associated with smaller hippocampal GMV and thicker vmPFC compared to a longer duration of use. For both GMV and CT of the right vmPFC, women with an early OC onset had more grey matter at a short duration of use than those with a later onset. Our results suggest that OC use earlier in adolescence may induce lasting effects on structural correlates of fear learning and its regulation. These findings support further investigation into the timing of OC use to better comprehend how OCs could disrupt normal brain development processes.

Genome-wide analysis identifies impaired axonogenesis in chronic overlapping pain conditions.

Chronic pain is often present at more than one anatomical location, leading to chronic overlapping pain conditions. Whether chronic overlapping pain conditions represent a distinct pathophysiology from the occurrence of pain at only one site is unknown. Using genome-wide approaches, we compared genetic determinants of chronic single-site versus multisite pain in the UK Biobank. We found that different genetic signals underlie chronic single-site and multisite pain with much stronger genetic contributions for the latter. Among 23 loci associated with multisite pain, nine loci replicated in the HUNT cohort, with the DCC netrin 1 receptor (DCC) as the top gene. Functional genomics identified axonogenesis in brain tissues as the major contributing pathway to chronic multisite pain. Finally, multimodal structural brain imaging analysis showed that DCC is most strongly expressed in subcortical limbic regions and is associated with alterations in the uncinate fasciculus microstructure, suggesting that DCC-dependent axonogenesis may contribute to chronic overlapping pain conditions via corticolimbic circuits.

Identification of traits and functional connectivity-based neurotraits of chronic pain.

Psychological and personality factors, socioeconomic status, and brain properties all contribute to chronic pain but have essentially been studied independently. Here, we administered a broad battery of questionnaires to patients with chronic back pain (CBP) and collected repeated sessions of resting-state functional magnetic resonance imaging (fMRI) brain scans. Clustering and network analyses applied on the questionnaire data revealed four orthogonal dimensions accounting for 56% of the variance and defining chronic pain traits. Two of these traits-Pain-trait and Emote-trait-were associated with back pain characteristics and could be related to distinct distributed functional networks in a cross-validation procedure, identifying neurotraits. These neurotraits showed good reliability across four fMRI sessions acquired over five weeks. Further, traits and neurotraits all related to the income, emphasizing the importance of socioeconomic status within the personality space of chronic pain. Our approach is a first step in providing metrics aimed at unifying the psychology and the neurophysiology of chronic pain applicable across diverse clinical conditions.

Morphometric network differences in ageing versus Alzheimer's disease dementia.

Age being the main risk factor for Alzheimer's disease, it is particularly challenging to disentangle structural changes related to normal brain ageing from those specific to Alzheimer's disease. Most studies aiming to make this distinction focused on older adults only and on a priori anatomical regions. Drawing on a large, multi-cohort dataset ranging from young adults (n = 468; age range 18-35 years), to older adults with intact cognition (n = 431; age range 55-90 years) and with Alzheimer's disease (n = 50 with late mild cognitive impairment and 71 with Alzheimer's dementia, age range 56-88 years), we investigated grey matter organization and volume differences in ageing and Alzheimer's disease. Using independent component analysis on all participants' structural MRI, we first derived morphometric networks and extracted grey matter volume in each network. We also derived a measure of whole-brain grey matter pattern organization by correlating grey matter volume in all networks across all participants from the same cohort. We used logistic regressions and receiver operating characteristic analyses to evaluate how well grey matter volume in each network and whole-brain pattern could discriminate between ageing and Alzheimer's disease. Because increased heterogeneity is often reported as one of the main features characterizing brain ageing, we also evaluated interindividual heterogeneity within morphometric networks and across the whole-brain organization in ageing and Alzheimer's disease. Finally, to investigate the clinical validity of the different grey matter features, we evaluated whether grey matter volume or whole-brain pattern was related to clinical progression in cognitively normal older adults. Ageing and Alzheimer's disease contributed additive effects on grey matter volume in nearly all networks, except frontal lobe networks, where differences in grey matter were more specific to ageing. While no networks specifically discriminated Alzheimer's disease from ageing, heterogeneity in grey matter volumes across morphometric networks and in the whole-brain grey matter pattern characterized individuals with cognitive impairments. Preservation of the whole-brain grey matter pattern was also related to lower risk of developing cognitive impairment, more so than grey matter volume. These results suggest both ageing and Alzheimer's disease involve widespread atrophy, but that the clinical expression of Alzheimer's disease is uniquely associated with disruption of morphometric organization.

The Stressful Characteristics of Pain That Drive You NUTS: A Qualitative Exploration of a Stress Model to Understand the Chronic Pain Experience.

OBJECTIVE: Despite decades of research on the identification of specific characteristics of situations that trigger a physiological stress response (novelty, unpredictability, threat to the ego, and sense of low control [NUTS]), no integrative research has examined the validity of this framework applied to pain experiences. This study aimed to 1) explore the stressful characteristics of pain among individuals living with chronic pain and 2) examine whether the NUTS framework comprehensively captures the stressful nature of pain. SUBJECTS: Participants were 41 adult participants living with chronic pain. METHODS: Interviews in six focus groups were conducted in French using a semistructured interview guide. Participants first discussed how pain is stressful. Then, they were introduced to the NUTS framework and commented on the extent to which it captured their experience. The verbatim transcriptions of interviews were reviewed using reflexive thematic analysis. Analyses were conducted in French; quotes and themes were translated into English by a professional translator. RESULTS: The pain-NUTS framework adequately captured participants' experiences. Multiple aspects of pain (pain intensity fluctuations, pain flare-up duration, pain quality and location, functional limitations, diagnosis and treatment) were associated with one or more stress-inducing characteristics. In addition, a second layer of meaning emerged in the context of chronic pain that provided contextual information regarding when, how, and why pain became more or less stressful. CONCLUSIONS: The NUTS characteristics seem to offer a comprehensive framework to understand how pain and its context of chronicity can be a source of stress. This study provides preliminary support for the pain-NUTS framework to allow the formal integration of pain and stress research.

Distinct fMRI patterns colocalized in the cingulate cortex underlie the after-effects of cognitive control on pain.

Demanding tasks can influence following behaviors but the underlying mechanisms remain largely unclear. In the present functional magnetic resonance imaging (fMRI) study, we used multivariate pattern analyses (MVPA) to compare patterns of brain activity associated with pain in response to noxious stimuli administered after a task requiring cognitive control (Stroop) and evaluate their functional interaction based on a mediation analysis model. We found that performing a difficult cognitive task leads to subsequent increases in pain and pain-related multivariate responses across the brain and within the anterior mid-cingulate cortex (aMCC). Moreover, an aMCC pattern predictive of task performance was further reactivated during pain and predicted ensuing increases in pain-related brain responses. This suggests functional interactions between distinct but partly co-localized neural networks underlying executive control and pain. These findings offer a new perspective on the functional role of the cingulate cortex in pain and cognition and provide a promising framework to investigate dynamical interactions between partly overlapping brain networks.

Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials.

Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo's effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active treatment in some patients diminishes modeled placebo-related analgesia. Trial Registration ClinicalTrials.gov NCT02903238 ClinicalTrials.gov NCT01558700.

Brain properties predict proximity to symptom onset in sporadic Alzheimer's disease.

See Tijms and Visser (doi:10.1093/brain/awy113) for a scientific commentary on this article.Alzheimer's disease is preceded by a lengthy 'preclinical' stage spanning many years, during which subtle brain changes occur in the absence of overt cognitive symptoms. Predicting when the onset of disease symptoms will occur is an unsolved challenge in individuals with sporadic Alzheimer's disease. In individuals with autosomal dominant genetic Alzheimer's disease, the age of symptom onset is similar across generations, allowing the prediction of individual onset times with some accuracy. We extend this concept to persons with a parental history of sporadic Alzheimer's disease to test whether an individual's symptom onset age can be informed by the onset age of their affected parent, and whether this estimated onset age can be predicted using only MRI. Structural and functional MRIs were acquired from 255 ageing cognitively healthy subjects with a parental history of sporadic Alzheimer's disease from the PREVENT-AD cohort. Years to estimated symptom onset was calculated as participant age minus age of parental symptom onset. Grey matter volume was extracted from T1-weighted images and whole-brain resting state functional connectivity was evaluated using degree count. Both modalities were summarized using a 444-region cortical-subcortical atlas. The entire sample was divided into training (n = 138) and testing (n = 68) sets. Within the training set, individuals closer to or beyond their parent's symptom onset demonstrated reduced grey matter volume and altered functional connectivity, specifically in regions known to be vulnerable in Alzheimer's disease. Machine learning was used to identify a weighted set of imaging features trained to predict years to estimated symptom onset. This feature set alone significantly predicted years to estimated symptom onset in the unseen testing data. This model, using only neuroimaging features, significantly outperformed a similar model instead trained with cognitive, genetic, imaging and demographic features used in a traditional clinical setting. We next tested if these brain properties could be generalized to predict time to clinical progression in a subgroup of 26 individuals from the Alzheimer's Disease Neuroimaging Initiative, who eventually converted either to mild cognitive impairment or to Alzheimer's dementia. The feature set trained on years to estimated symptom onset in the PREVENT-AD predicted variance in time to clinical conversion in this separate longitudinal dataset. Adjusting for participant age did not impact any of the results. These findings demonstrate that years to estimated symptom onset or similar measures can be predicted from brain features and may help estimate presymptomatic disease progression in at-risk individuals.

Hippocampal morphology mediates biased memories of chronic pain.

Experiences and memories are often mismatched. While multiple studies have investigated psychological underpinnings of recall error with respect to emotional events, the neurobiological mechanisms underlying the divergence between experiences and memories remain relatively unexplored in the domain of chronic pain. Here we examined the discrepancy between experienced chronic low back pain (CBP) intensity (twice daily ratings) and remembered pain intensity (n = 48 subjects) relative to psychometric properties, hippocampus morphology, memory capabilities, and personality traits related to reward. 77% of CBP patients exaggerated remembered pain, which depended on their strongest experienced pain and their most recent mood rating. This bias persisted over nearly 1 year and was related to reward memory bias and loss aversion. Shape displacement of a specific region in the left posterior hippocampus mediated personality effects on pain memory bias, predicted pain memory bias in a validation CBP group (n = 21), and accounted for 55% of the variance of pain memory bias. In two independent groups (n = 20/group), morphology of this region was stable over time and unperturbed by the development of chronic pain. These results imply that a localized hippocampal circuit, and personality traits associated with reward processing, largely determine exaggeration of daily pain experiences in chronic pain patients.

Corticolimbic anatomical characteristics predetermine risk for chronic pain.

SEE TRACEY DOI101093/BRAIN/AWW147 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Mechanisms of chronic pain remain poorly understood. We tracked brain properties in subacute back pain patients longitudinally for 3 years as they either recovered from or transitioned to chronic pain. Whole-brain comparisons indicated corticolimbic, but not pain-related circuitry, white matter connections predisposed patients to chronic pain. Intra-corticolimbic white matter connectivity analysis identified three segregated communities: dorsal medial prefrontal cortex-amygdala-accumbens, ventral medial prefrontal cortex-amygdala, and orbitofrontal cortex-amygdala-hippocampus. Higher incidence of white matter and functional connections within the dorsal medial prefrontal cortex-amygdala-accumbens circuit, as well as smaller amygdala volume, represented independent risk factors, together accounting for 60% of the variance for pain persistence. Opioid gene polymorphisms and negative mood contributed indirectly through corticolimbic anatomical factors, to risk for chronic pain. Our results imply that persistence of chronic pain is predetermined by corticolimbic neuroanatomical factors.

Empathy in paediatric intensive care nurses part 1: Behavioural and psychological correlates.

AIM: To determine if differences exist between paediatric intensive care nurses and allied health professionals in empathy, secondary trauma, burnout, pain exposure and pain ratings of self and others. Early and late career differences were also examined. BACKGROUND: Nurses are routinely exposed to patient pain expression. This work context may make them vulnerable to adverse outcomes such as desensitization to patient pain or a compromise in personal well-being. DESIGN: Cross-sectional study. METHODS: Data were collected from a convenience sample of paediatric intensive care nurses (n = 27) and allied health professionals (n = 24), from September 2014-June 2015, at a Canadian health centre. Both groups completed one demographic and three behavioural scales. Participants underwent fMRI while rating the pain of infant and adult patients in a series of video clips. Data were analyzed using parametric and non-parametric methods. fMRI results are reported in a second paper. RESULTS: Nurses were significantly more likely to be exposed to pain at work than allied health professionals and scored significantly higher on dimensions of empathy, secondary trauma and burnout. Nurses scored their own pain and the pain of infant and adult patients, higher than allied health participants. Less experienced nurses had higher secondary trauma and burnout scores than more experienced nurses. CONCLUSIONS: Paediatric intensive care work demands, such as patient pain exposure, may be associated with nurse's higher report of empathy and pain in self and others, but also with higher levels of secondary trauma and burnout, when compared with allied health professionals.

Empathy in paediatric intensive care nurses part 2: Neural correlates.

AIMS: To determine if there are brain activity differences between paediatric intensive care nurses and allied health professionals during pain intensity rating tasks and test whether these differences are related to the population observed (infant or adult) and professional experience. BACKGROUND: The underestimation of patients' pain by healthcare professionals has generally been associated with patterns of change in neural response to vicarious pain, notably reduced activation in regions associated with affective sharing and increased activation in regions associated with regulation, compared with controls. Paediatric nurses, however, have recently been found to provide higher estimates of infants' pain in comparison to allied health controls, suggesting that changes in neural response of this population might be different than other health professionals. DESIGN: Cross-sectional study. METHODS: Functional MRI data were acquired from September 2014-June 2015 and used to compare changes in brain activity in 27 female paediatric care nurses and 24 allied health professionals while rating the pain of infants and adults in a series of video clips. RESULTS: Paediatric nurses rated infant and adult pain higher than allied health professionals, but the two groups' neural response only differed during observation of infant pain; paediatric nurses mainly showed significantly less activation in the medial prefrontal cortex (linked to cognitive empathy) and in the left anterior insula and inferior frontal cortex (linked to affective sharing). CONCLUSIONS: Patterns of neural activity to vicarious pain may vary across healthcare professions and patient populations and the amount of professional experience might explain part of these differences.

Acute stress contributes to individual differences in pain and pain-related brain activity in healthy and chronic pain patients.

Individual differences in pain sensitivity and reactivity are well recognized but the underlying mechanisms are likely to be diverse. The phenomenon of stress-induced analgesia is well documented in animal research and individual variability in the stress response in humans may produce corresponding changes in pain. We assessed the magnitude of the acute stress response of 16 chronic back pain (CBP) patients and 18 healthy individuals exposed to noxious thermal stimulations administered in a functional magnetic resonance imaging experiment and tested its possible contribution to individual differences in pain perception. The temperature of the noxious stimulations was determined individually to control for differences in pain sensitivity. The two groups showed similar significant increases in reactive cortisol across the scanning session when compared with their basal levels collected over 7 consecutive days, suggesting normal hypothalamic-pituitary-adrenal axis reactivity to painful stressors in CBP patients. Critically, after controlling for any effect of group and stimulus temperature, individuals with stronger cortisol responses reported less pain unpleasantness and showed reduced blood oxygenation level-dependent activation in nucleus accumbens at the stimulus onset and in the anterior mid-cingulate cortex (aMCC), the primary somatosensory cortex, and the posterior insula. Mediation analyses indicated that pain-related activity in the aMCC mediated the relationship between the reactive cortisol response and the pain unpleasantness. Psychophysiological interaction analysis further revealed that higher stress reactivity was associated with reduced functional connectivity between the aMCC and the brainstem. These findings suggest that acute stress modulates pain in humans and contributes to individual variability in pain affect and pain-related brain activity.

The stress model of chronic pain: evidence from basal cortisol and hippocampal structure and function in humans.

Recent theories have suggested that chronic pain could be partly maintained by maladaptive physiological responses of the organism facing a recurrent stressor. The present study examined the associations between basal levels of cortisol collected over seven consecutive days, the hippocampal volumes and brain activation to thermal stimulations administered in 16 patients with chronic back pain and 18 healthy control subjects. Results showed that patients with chronic back pain have higher levels of cortisol than control subjects. In these patients, higher cortisol was associated with smaller hippocampal volume and stronger pain-evoked activity in the anterior parahippocampal gyrus, a region involved in anticipatory anxiety and associative learning. Importantly, path modelling-a statistical approach used to examine the empirical validity of propositions grounded on previous literature-revealed that the cortisol levels and phasic pain responses in the parahippocampal gyrus mediated a negative association between the hippocampal volume and the chronic pain intensity. These findings support a stress model of chronic pain suggesting that the sustained endocrine stress response observed in individuals with a smaller hippocampii induces changes in the function of the hippocampal complex that may contribute to the persistent pain states.

Modulating subjective pain perception with decoded Montreal Neurological Institute-space neurofeedback: a proof-of-concept study.

Pain is a complex emotional experience that still remains challenging to manage. Previous functional magnetic resonance imaging (fMRI) studies have associated pain with distributed patterns of brain activity (i.e. brain decoders), but it is still unclear whether these observations reflect causal mechanisms. To address this question, we devised a new neurofeedback approach using real-time decoding of fMRI data to test if modulating pain-related multivoxel fMRI patterns could lead to changes in subjective pain experience. We first showed that subjective pain ratings can indeed be accurately predicted using a real-time decoding approach based on the stimulus intensity independent pain signature (SIIPS) and the neurologic pain signature (NPS). Next, we trained participants (n = 16) in a double-blinded decoded fMRI neurofeedback experiment to up- or downregulate the SIIPS. Our results indicate that participants can learn to downregulate the expression of SIIPS independently from NPS expression. Importantly, the success of this neurofeedback training was associated with the perceived intensity of painful stimulation following the intervention. Taken together, these results indicate that closed-loop brain imaging can be efficiently conducted using a priori fMRI decoders of pain, potentially opening up a new range of applications for decoded neurofeedback, both for clinical and basic science purposes. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Predicting placebo analgesia in patients with chronic pain using natural language processing: a preliminary validation study.

ABSTRACT: Patients with chronic pain show large placebo effects in clinical trials, and inert pills can lead to clinically meaningful analgesia that can last from days to weeks. Whether the placebo response can be predicted reliably, and how to best predict it, is still unknown. We have shown previously that placebo responders can be identified through the language content of patients because they speak about their life, and their pain, after a placebo treatment. In this study, we examine whether these language properties are present before placebo treatment and are thus predictive of placebo response and whether a placebo prediction model can also dissociate between placebo and drug responders. We report the fine-tuning of a language model built based on a longitudinal treatment study where patients with chronic back pain received a placebo (study 1) and its validation on an independent study where patients received a placebo or drug (study 2). A model built on language features from an exit interview from study 1 was able to predict, a priori, the placebo response of patients in study 2 (area under the curve = 0.71). Furthermore, the model predicted as placebo responders exhibited an average of 30% pain relief from an inert pill, compared with 3% for those predicted as nonresponders. The model was not able to predict who responded to naproxen nor spontaneous recovery in a no-treatment arm, suggesting specificity of the prediction to placebo. Taken together, our initial findings suggest that placebo response is predictable using ecological and quick measures such as language use.

Facial expression is a distinctive behavioural marker of pain processing in the brain.

Pain is a private experience observable through various verbal and non-verbal behavioural manifestations. Despite the importance of understanding the cerebral mechanisms underlying those manifestations, there is currently limited knowledge on the neural correlates of facial expression of pain. Here, we applied a brain decoding approach to functional magnetic resonance imaging (fMRI) data to predict the facial expression of pain during noxious heat stimulation in healthy volunteers. Results revealed the inability of previously developed pain neurosignatures to predict the facial expression of pain. We thus propose a Facial Expression of Pain Signature (FEPS) conveying distinctive information about the brain response to nociceptive stimulations with minimal overlap with other pain-relevant brain signatures. The FEPS provides a better characterization of the distributed cerebral representations of non-verbal pain communication. This underscores the complexity of pain phenomenology by reinforcing the view that neurosignatures conceived as biomarkers must be interpreted in relation to the specific pain manifestation predicted.

Functional connectome fingerprinting across the lifespan.

Systematic changes have been observed in the functional architecture of the human brain with advancing age. However, functional connectivity (FC) is also a powerful feature to detect unique "connectome fingerprints," allowing identification of individuals among their peers. Although fingerprinting has been robustly observed in samples of young adults, the reliability of this approach has not been demonstrated across the lifespan. We applied the fingerprinting framework to the Cambridge Centre for Ageing and Neuroscience cohort (n = 483 aged 18 to 89 years). We found that individuals are "fingerprintable" (i.e., identifiable) across independent functional MRI scans throughout the lifespan. We observed a U-shape distribution in the strength of "self-identifiability" (within-individual correlation across modalities), and "others-identifiability" (between-individual correlation across modalities), with a decrease from early adulthood into middle age, before improving in older age. FC edges contributing to self-identifiability were not restricted to specific brain networks and were different between individuals across the lifespan sample. Self-identifiability was additionally associated with regional brain volume. These findings indicate that individual participant-level identification is preserved across the lifespan despite the fact that its components are changing nonlinearly.

A prognostic risk score for development and spread of chronic pain.

Chronic pain is a complex condition influenced by a combination of biological, psychological and social factors. Using data from the UK Biobank (n = 493,211), we showed that pain spreads from proximal to distal sites and developed a biopsychosocial model that predicted the number of coexisting pain sites. This data-driven model was used to identify a risk score that classified various chronic pain conditions (area under the curve (AUC) 0.70-0.88) and pain-related medical conditions (AUC 0.67-0.86). In longitudinal analyses, the risk score predicted the development of widespread chronic pain, the spreading of chronic pain across body sites and high-impact pain about 9 years later (AUC 0.68-0.78). Key risk factors included sleeplessness, feeling 'fed-up', tiredness, stressful life events and a body mass index >30. A simplified version of this score, named the risk of pain spreading, obtained similar predictive performance based on six simple questions with binarized answers. The risk of pain spreading was then validated in the Northern Finland Birth Cohort (n = 5,525) and the PREVENT-AD cohort (n = 178), obtaining comparable predictive performance. Our findings show that chronic pain conditions can be predicted from a common set of biopsychosocial factors, which can aid in tailoring research protocols, optimizing patient randomization in clinical trials and improving pain management.